The broad aim of this proposal is to understand the cognitive and neural systems that support incremental, feedback-based learning. Recent evidence suggests that this type of learning depends on the basal ganglia (BG) - primarily the striatum and its dopaminergic afferents. By contrast, a distinct and independent memory system in the medial temporal lobe (MTL) is thought to support rapidly formed memories of single-trial episodes. However, recent studies have shown that this dichotomy may be oversimplified, and that in many cases the BG and the MTL both contribute to learning. Thus, fundamental questions remain regarding the circumstances under which each of these systems support learning and the implications of their involvement for the representation of knowledge. Bridging across electrophysiological data, computational modeling, and human neuropsychology, the proposed research aims to test the hypothesis that a critical factor driving learning to depend on one system or the other is the timing of response-contingent feedback. The studies herein seek to test this hypothesis by systematically investigating how the timing of feedback (immediate vs. delayed) modulates different aspects of learning and memory. Our model system is healthy older adults and individuals with Parkinson's disease, who suffer from disrupted BG function but have intact MTL function. We will further examine both chronic and acute dopamine perturbations by examining how dopaminergic medication modulates feedback-based learning in Parkinson's patients. Finally, we aim to determine the cognitive mechanisms involved under different delay conditions, comparing incremental and episodic learning. The resulting findings are expected to enhance our understanding of the cognitive and neural systems supporting feedback-based learning, and how these are modulated by BG dysfunction and dopaminergic mechanisms. PUBLIC HEALTH RELEVANCE: Parkinson's disease is characterized by a range of learning deficits. The resulting findings will provide insight into the nature, and possible cause, of these deficits, as well as how they are impacted by medication. Understanding the basic mechanisms of feedback-based learning is also relevant to other diseases that affect large segments of the population, such as Alzheimer's disease, depression, and schizophrenia - all characterized by learning and memory problems. By understanding how people learn in different ways as a result of changes in feedback information and how brain chemistry affects this learning, we can better understand how to help those already suffering from such diseases and contribute to better treatments in the future.